code: def update_dataset_props(
      dataset_props: dict, default_dataset_props: dict
  ):
      for key1 in default_dataset_props.keys():
          if key1 in dataset_props.keys():
              for key2 in default_dataset_props[key1].keys():
                  if key2 in dataset_props[key1].keys():
                      default_dataset_props[key1][key2] = dataset_props[
                          key1
                      ][key2]
  
      return default_dataset_props
  
file_path: igel/igel/preprocessing.py
imports: import logging
  import numpy
  import pandas
  from sklearn.impute import SimpleImputer
  from sklearn.preprocessing import LabelEncoder, MinMaxScaler, OneHotEncoder, StandardScaler
label_desc: Use image node_id 2 for calling a global function with example usage: update_dataset_props(dataset_props, default_dataset_props) and returns: default_dataset_props